Artificial Intelligence Engineer

AI Engineer Generative AI & Agentic Systems Indicative UK salary: £80,000–£100,000 per annum The opportunity We are looking for a hands-on AI Engineer to build, integrate, test and deploy production-grade AI applications for enterprise use cases. Working alongside architects, domain specialists and engineering teams, you will turn approved designs into reliable working software. The role spans Python development, LLM integration, AI agents, retrieval pipelines, enterprise APIs, automated evaluation and cloud deployment. This is an engineering-focused opportunity for someone who enjoys solving practical problems and taking AI solutions from technical specification through to production and handover. Key responsibilities - Build and deploy AI-enabled applications, back-end services, APIs and orchestration components. - Develop AI agents and workflows incorporating tools, state, memory, delegation, retries and human approval. - Implement RAG and knowledge pipelines for structured and unstructured data, including ingestion, parsing, chunking, indexing, retrieval and ranking. - Integrate LLM endpoints and enterprise AI services, implementing prompt and model configuration, routing and fallback mechanisms. - Build integrations with enterprise systems using REST or gRPC APIs, microservices, events, queues and other approved patterns. - Develop data ingestion and transformation pipelines with validation, data-quality checks and schema-change handling. - Write clean, modular, testable and maintainable code. - Create unit, integration, regression, security and performance tests for AI applications. - Develop evaluation datasets and automated checks for retrieval quality, groundedness, task success, safety and cost. - Implement logging, metrics, tracing, dashboards and alerts to support monitoring and troubleshooting. - Support containerisation, CI/CD, cloud deployment, release management and rollback procedures. - Investigate and resolve issues across data pipelines, retrieval, models, prompts, integrations and infrastructure. - Contribute reusable code, connectors, agent templates, technical documentation and operational runbooks. Essential experience - 6–12 years of software, data, machine learning or platform engineering experience. - Strong hands-on Python development skills. - Practical experience delivering LLM, generative AI, RAG, agentic AI or machine learning applications beyond tutorials or isolated notebooks. - Experience integrating AI models or services with APIs, enterprise applications, data sources and business workflows. - Experience with REST or gRPC, databases, asynchronous processing or event-driven systems. - Familiarity with automated testing, version control, code reviews, containers and CI/CD. - Practical experience with AWS, Microsoft Azure or Google Cloud. - Understanding of SQL, data processing, retrieval, embeddings and vector or hybrid search. - Experience with logging, monitoring, troubleshooting and production deployment. - Understanding of AI security risks, including prompt injection, hallucinations, data leakage and safe fallback patterns. - Strong communication skills and the ability to take ownership of technical deliverables through build, testing, deployment and handover. Desirable experience - Front-end development using React, Angular, Vue, Next.js or similar frameworks. - Experience with agent frameworks, tool calling, model gateways or LLMOps. - Exposure to streaming, distributed processing, knowledge graphs or document intelligence. - Experience with conversational AI, voice AI or multimodal applications. - Experience in regulated, security-sensitive or high-availability environments. - Relevant cloud, AI engineering, data engineering, DevOps or application-security certifications. What we are looking for A practical engineer who can turn AI designs into working, production-ready software. You should be comfortable debugging complex issues, evaluating AI quality, improving reliability and collaborating with architects and stakeholders to deliver measurable outcomes. Employment type: Permanent Location and working arrangement: To be confirmed Travel: Willingness to travel according to client and project requirements